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The Complete Course: Artificial Intelligence From Scratch (Udemy.com)

Learn the Essential Concepts of the AI like Neural Networks, Classification, Regression and Optimization Using Python.

3.5
55 reviews

Created by: Sobhan N.

Last updated December 2018

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What you will learn

  • Learn the basic of Artificial Intelligence from scratch.
  • Learn how Neural Networks work.
  • Program Multilayer Perceptron Network from scratch in python.
  • You'll know how recurrent neural networks work.
  • You'll learn how to create LSTM networks using python and Keras
  • You'll know how to forecast Google stock price with high accuracy
  • Use k Nearest Neighbor classification method to classify datasets.
  • Classify datasets by using Support Vector Machine method
  • Understand main concept behind Support Vector Machine method.
  • Classify Handwritten Images by Logistic classification method
  • You'll know how Linear Regression work.
  • You'll know how Multi Linear Regression work using sklearn and Python.
  • Program Logistic Regression from scratch in python.
  • Build Model to Predict CO2 and Global Temperature by Polynomial Regression.
  • You'll know the ideas behind Genetic Algorithm.

How it compares

Against the other 205 rated Udemy courses in Artificial Intelligence on CourseDuck:

  • Rating3.5 out of 5higher than 1% of them
  • Reviews55#185 of 206 by number of reviews
  • Length14.3 hourslonger than 82% of them
  • Last updatedDecember 2018earlier than 95% of them

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Quality Score

Content Quality
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Video Quality
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Qualified Instructor
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Overall Score : 70 / 100

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Course Description

Do you like to learn how to forecast economic time series like stock price or indexes with high accuracy?
Do you like to know how to predict weather data like temperature and wind speed with a few lines of codes?
Do you like to classify Handwritten digits more accurately ?
If you say Yes so read more ...

In computer science, Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In this you are going to learn essential concepts of AI using Python:
Neural Networks
Classification Methods
Regression Analysis
Optimization Methods
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in the First, Second,Third sections you will learn Neural Networks
You will learn how to make Recurrent Neural Networks using Keras and LSTMs:
  • you'll learn how to use python and Keras to forecast google stock price .

  • you'll know how to use python and Keras to predict NASDAQ Index precisely.

  • you'll learn how to use python and Keras to forecast New York temperature with low error.

  • you'll know how to use python and Keras to predict New York Wind speed accurately.

In the next section you learn how to use python and sklearn MLPclassifier to forecast output of different datasets like
  • Logic Gates
  • Vehicles Datasets
  • Generated Datasets
In the third section you can forecast output of different datasets using Keras library like
  • Random datasets
  • Forecast International Airline passengers
  • Los Angeles temperature forecasting
_____________________________________________________________________________________________________________________
Next you will learn how to classify well known datasets into with high accuracy using k-Nearest Neighbors, Bayes, Support Vector Machine and Logistic Regression.
In the 4th section you learn how to use python and k-Nearest Neighbors to estimate output of your system. In this section you can classify:
  • Python Dataset
  • IRIS Flowers
  • Make your own k Nearest Neighbors Algorithm
In the 5th section you learn how to use Bayes and python to classify output of your system with nonlinear structure .In this section you can classify:
  • IRIS Flowers
  • Pima Indians Diabetes Database
  • Make your own Naive Bayes Algorithm
You can also learn how to classify datasets by by Support Vector Machines to find the correct class for data and reduce error. Next you go further You will learn how to classify output of model by using Logistic Regression
In the 6th section you learn how to use python to estimate output of your system. In this section you can estimate output of:
  • Random dataset
  • IRIS Flowers
  • Handwritten Digits
In the 7th section you learn how to use python to classify output of your system with nonlinear structure .In this section you can estimate output of:
  • Blobs
  • IRIS Flowers
  • Handwritten Digits
_____________________________________________________________________________________________________________________
After it we are going to learn regression methods like Linear, Multi-Linear and Polynomial Regression.
In the 8th section you learn how to use Linear Regression and python to estimate output of your system. In this section you can estimate output of:
  • Random Number
  • Diabetes
  • Boston House Price
  • Built in Dataset
In the 9th section you learn how to use python and Multi Linear Regression to estimate output of your system with multivariable inputs.In this section you can estimate output of:
  • Global Temprature
  • Total Sales of Advertising Campaign
  • Built in Dataset
In the 10th section you learn how to use python Polynomial Regression to estimate output of your system. In this section you can estimate output of:
  • Nonlinear Sine Function
  • Python Dataset
  • Temperature and CO2
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Finally I want to learn you theory behind bio inspired algorithms like Genetic Algorithm and Particle Swarm Optimization Method. You'll learn basic genetic operators like mutation crossover and selection and how they are work. You'll learn basic concepts of Particle Swarm and how they are work.
In the 11th section you will learn how to use python and deap library to solve optimization problem and find Min/Max points for your desired functions using Genetic Algorithm.
  • you'll learn theory of Genetic Algorithm Optimization Method

  • you'll know how to use python and deap to optimize simple function precisely.

  • you'll learn how to use python and deap to find optimum point of complicated Trigonometric function.

  • you'll know how to use python and deap to solve Travelling Salesman Problem (TSP) accurately.

In the 12th section we go further you will learn how to use python and deap library to solve optimization problem using Particle Swarm Optimization
  • you'll learn theory of Particle Swarm Optimization Method

  • you'll know how to use python and deap to optimize simple function precisely.

  • you'll learn how to use python and deap to find optimum point of complicat
Read More All Levels All Levels product length iconTime: 14.3h

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Instructor Details

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My passion is teaching people through online courses. I love learning new skills, and since 2015 have been teaching people like you everything. I create courses that teach you how to become the better version of yourself with all kinds of skills.
What would you like to learn?
Would you like to learn Artificial Intelligence in python?
Would you like to make money creating landing pages?
Would you like to build your own AI programs & do something awesome for you?
Would you like to learn Xamarin to make both iOS/Android apps?
Would you like to learn how to write codes in HTML5 and CSS3?
Would you like to learn MATLAB the scientific language for researchers?

If you want to do any of these things, just enroll in the course. You have a 30-day money back guarantee if you don't like it. And I'm always improving my courses so that they stay up to date and the best that they can be. Check them out, and enroll today!
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About Sobhan N:
I have PhD degree in Electrical Engineering and like to learn anything about Electronics, Programming and Artificial Intelligence. I like electronic stuff like Arduino, Raspberry Pi and microcontrollers.
My passion is

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Reviews

3.5

55 ratings on Udemy

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By Miguel Ángel González Cagigal

El audio es muy mejorable

By Fran Li

Better to have some simple examples when illustrating the concepts.

By Vincent Doherty

It very advanced course. There is a lot of code which is not explained what it does.

By Tharindu Buddhika Adhikari

This course is amazing and above my expectations! Very good exercises, good speed, well communicated. The instructor made me feel very comfortable and was able to take many things away. Excellent content and very knowledgeable instructor!

By Muhammad Younas

Great course

By Diego R Midence Hernandez

This course is fairly good if you have poor python programming experience and you want to start coding in python to solve any given problem because you are driven from scratch to code a program to solve a concrete problem using a specific algorithm of artificial intelligence.

However, If you are looking for a more challenging course in artificial intelligence and python, this course is not for you.

The course should be improved since there are many steps that are repetitive in all the lectures. These steps should be summarized and only mentioned. This could make the video lectures shorter and avoid boredom.

Although the last two sections regarding genetic algorithms and particle swarm optimization were a bonus, from my point of view, the lectures hardly explain the theoretical concepts and how they were coded in the python program. You have to figure out that.

Despite that, I realize that is available in internet the "DEAP" library, which is the core library used in the lectures, with full of references to learn to use it.

In general, this course has a very good benefits-cost relationship. Therefore, I would recommend it as start point in python coding to use artificial intelligence algorithm.

By Chaman Lal Dewangan

Presentation background and typesetting are annoying.

Just reading presentation is not a good method.

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The Complete Course: Artificial Intelligence From Scratch
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  • Video Duration: icon 14.3h
  • Price: $39.99
  • Provider: icon Udemy
  • Updated: icon December 2018
  • Level: All Levels All Levels
  • Language: icon English
  • Certificate: icon Yes
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